Biology subjects

Xu, L.

Publications and source records attributed to Xu, L..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Homeobox transcription factor MSX2 down-regulates ERα action to facilitate anti-estrogensensitivity in ERα+ breast cancer

Breast cancer is the most common malignancy among women worldwide. Estrogen receptor (ER)-positive breast cancer is about 70% in the total breast cancer. It has variable prognosis and high recurrent risk, frequently developing resistance to endocrine therapies. Herein, we have identified that a homeobox transcription factor MSX2 downregulated in ER-positive breast cancer is correlated with the advanced grade and poor survival outcomes. Our results have demonstrated that MSX2 interacts with ER to inhibit ER-mediated transactivation. Mechanistically, MSX2 associates with HDAC1/HDAC2 to form a protein complex. MSX2 is required for recruitment of HDAC1/HDAC2 complex to estrogen response elements (EREs) region on ER downstream target genes, reducing histone H3K9ac and H3K27ac levels to inactivate gene transcription. Functionally, ectopic expression of MSX2 suppresses cell growth and enhances the sensitivity to anti-estrogen treatment in ER-positive breast cancer cells. Our results indicate that MSX2 as a novel co-repressor of ER is involved in suppression of ER-positive breast cancer progression. Restoring MSX2 protein may provide a promising strategy to overcome endocrine resistance in ER-positive breast cancer.

Molecular Biology↗

bioRxiv2026

PHI-Reason: evidence-grounded species-level phage-host prediction from structured biological text profiles

Biological interaction inference often requires integrating heterogeneous evidence that differs in biological meaning, provenance, specificity, and reliability. Existing computational approaches typically compress such evidence into numerical features, aggregate scores or latent representations before prediction, obscuring the contribution of individual evidence records and limiting interpretation when evidence is conflicting or incomplete. Phage-host interaction prediction provides a demanding test case for this problem, requiring the integration of genomic, functional, and reference-derived evidence with differing coverage, specificity, and reliability. Here we introduce a structured-evidence inference paradigm that retains heterogeneous biological observations as modular, named, and experimentally perturbable records rather than compressing them before prediction. We implement this paradigm in PHI-Reason, which constructs structured evidence profiles from genomic annotations, receptor-binding protein homology, nucleotide-neighbour relationships, alignment-free genomic similarity, and available CRISPR spacer information. A general-purpose large language model (LLM) performs inference directly over these structured profiles without task-specific training or manually engineered evidence-fusion rules. To validate this paradigm, we evaluated it across two distinct biological interaction domains: prokaryotic phage-host prediction and eukaryotic virus-host prediction. Across phage-host benchmarks, PHI-Reason achieved species-level top-1 accuracies of 63.6% and 53.2% on RefSeq-634 and VHDB-3150, respectively, and a multi-host accuracy of 0.571 on the Hi-C cohort, outperforming established numerical methods. Besides, systematic evidence perturbations quantified how individual evidence supported, complemented, or misled inference, identifying nucleotide-neighbour context as the dominant signal. Analyses of LLM intermediate representations using a target-conditioned local Jacobian readout, together with output-grounding analyses, further characterized evidence-dependent inference and quantified the extent to which generated rationales departed from the supplied evidence profiles. Applying the same framework to eukaryotic virus-host prediction using domain-appropriate evidence also preserved high predictive accuracy (66.6%), supporting the generalizability of the proposed paradigm across biological prediction. These results demonstrate that LLMs can serve as an evidence-grounded inference interface, integrating heterogeneous biological evidence while making the boundaries of evidential support directly testable.

bioinformatics↗

bioRxiv2026

Transient suppression of the ECM1 gatekeeper is essential for HGF/c-MET-driven liver regeneration

Hepatocyte growth factor (HGF) is a multifunctional cytokine stored in the extracellular matrix as an inactive precursor and is essential for tissue repair. How HGF activity is dynamically regulated during regeneration remains unclear. Here, we identify extracellular matrix protein 1 (ECM1) as a physiological inhibitor of active HGF during liver regeneration. Following 70% partial hepatectomy, active HGF rapidly increases in parallel with a sharp decline in ECM1, and preventing this downregulation delays liver mass recovery. Mechanistically, ECM1 directly binds the active HGF -subunit through a mechanism dependent on residue R392, thereby suppressing c-MET-ERK-MYC signaling and hepatocyte proliferation. Loss of ECM1 permits activation of this pathway, whereas MYC overexpression rescues ECM1-mediated growth inhibition. In patients, proliferative hepatocytes localize to ECM1-negative regions. Supported by transcriptomic analyses and computational modeling, these findings identify ECM1 as an extracellular gatekeeper whose transient downregulation enables HGF-driven tissue repair. HighlightsO_LIECM1 is temporally downregulated during liver regeneration, while forced ECM1 expression delays liver mass recovery after 70% PHx by suppressing hepatocyte proliferation. C_LIO_LIRapid and transient ECM1 downregulation permits HGF-c-Met-ERK-MYC signaling to drive hepatocyte cell-cycle entry and expansion. C_LIO_LIECM1 directly binds the active HGF -subunit with residue R392 playing a critical role, revealing a novel extracellular mechanism for growth factor inhibition. C_LIO_LILoss of ECM1 marks proliferative hepatocytes in human liver repair, identifying ECM1 as a tunable regulator of regenerative capacity. C_LI

cell biology↗

bioRxiv2026

Retinoid signaling promotes frontonasal identity while repressing maxillary identity during craniofacial development

Vertebrate facial development depends on the correct specification of embryonic facial prominences, a process known to be governed by region-specific reciprocal signaling pathways between the craniofacial ectoderm, endoderm and mesenchyme. This process is further modulated by transcriptional and epigenetic mechanisms that regulate the expression of essential genes in mesenchymal progenitors derived from cranial neural crest cells. Retinoid signaling plays a critical role in facial development, and both gain-and loss-of-function results in a wide spectrum of facial defects, including orofacial clefts. In this study, we identified retinoid signaling as a critical regulator of cranial neural crest cell specification toward a frontonasal process identity in mice. Rdh10 oxidizes vitamin A (all-trans retinol) to retinal, which is a rate limiting step in the synthesis of retinoic acid. Rdh10 loss-of-function resulted in ectopic formation of whisker pads - a derivative of the maxillary process - within the frontonasal process region. This transformation was evidenced by the mis-expression of maxillary specific transcription factors including Meis2 and Lhx6 in the frontonasal mesenchyme. Furthermore, these transcription factors exhibited increased chromatin accessibility at their consensus binding sites following the loss of retinoid signaling in frontonasal cranial neural crest cells. These results indicate that retinoid signaling acts as a critical regulator specifying frontonasal identity and fate of cranial neural crest cells as they migrate into the frontonasal process, while concomitantly repressing maxillary process fate. These results not only advance our understanding of frontonasal prominence specification and the evolutionary development of craniofacial structures but also offers valuable insights into the etiology and pathogenesis of craniofacial malformations such as orofacial clefts.

developmental biology↗

bioRxiv2026

Hypothalamic MCH neurons links tau pathology to sleep disruption

Sleep disruption is an early and pervasive feature of Alzheimers disease (AD), yet the circuit mechanisms linking tau pathology to sleep-wake dysfunction remain unresolved. Here, we identify melanin-concentrating hormone (MCH) neurons in the lateral hypothalamus (LH) as a critical node disrupted in tauopathy. Longitudinal EEG/EMG recordings in PS19 mice reveal progressive impairments in sleep architecture and homeostasis. Histological analyses revealed significant degeneration of both MCH neurons and the neighboring hypocretin (Hcrt) neuronal population in the LH at late stages of tauopathy. In vivo fiber photometry recordings demonstrated a selective functional impairment of MCH neurons, characterized by reduced activity during REM sleep, whereas Hcrt neuronal activity remained largely preserved. In addition, cell-autonomous expression of mutant tau in MCH neurons recapitulates sleep disruption, establishing a causal role. Despite tauopathy-induced neuronal loss and reduced endogenous activity, optogenetic and chemogenetic activation show that MCH neurons retain functional capacity, and their activation restores sleep in aged PS19 mice. Together, these findings define a circuit mechanism linking tau pathology to sleep and identify MCH neurons as a tractable therapeutic target.

neuroscience↗

bioRxiv2026

Extracellular Vesicle Biomarkers in the Aqueous Humor Correlate with Retinoblastoma Seeding

PurposeTo investigate the correlation of retinoblastoma (RB) aqueous humor (AH)-derived extracellular vesicle (EV) surface markers, particularly CD133, with clinical features of RB. MethodsAH samples (n=22) collected at diagnosis (n=17) or primary enucleation (n=5) from RB eyes were profiled using magnetic bead-based flow cytometry. Median fluorescence intensities (MFI) of tetraspanins (CD9, CD63, CD81) and CD133 were quantified and correlated with International Intraocular RB Classification (IIRC) stage, seeding location, seeding morphology, and enucleation. ResultsCD133+ EVs were detected in 16 of 22 (73%) samples. While CD133 levels showed a non-significant increasing trend with advanced IIRC stages, CD133 expression was significantly elevated in eyes with vitreous seeding vs. subretinal only (P = 0.010). Cuzicks trend analysis revealed a significant association between rising CD133 % MFI and complex seeding (P < 0.001). Conversely, CD63 displayed a significant inverse trend, with decreasing % MFI associated with complex seeding (P < 0.001). CD133high eyes (MFI>10,000, n=9) exhibited increased enucleation (P = 0.007) and predominantly sphere/cloud seeding patterns (P = 0.001). CD133high eyes demonstrated a coordinated CD63/CD81 co-expression pattern (r = 0.80), absent in the CD133low group. ConclusionsElevated CD133 level and percentage were associated with vitreous involvement and complex seeding morphology, suggesting potential as a minimally invasive indicator of disease burden. The inverse relationship between CD63 and seeding severity, combined with CD63/CD81 remodeling in CD133high eyes, suggests an EV profile indicative of aggressive disease. These findings support the association of CD133+ EVs with advanced RB seeding and warrant further prospective validation.

cancer biology↗

bioRxiv2026

Efficient and accurate near telomere-to-telomere haplotype reconstruction of diploid genomes

Telomere-to-telomere (T2T) and haplotype-resolved assembly are crucial for understanding eukaryotic genomes. For diploid species, this resolution is critical to uncover allelic variations, inheritance patterns, and functional genomic traits. Current scaffolding methods typically employ either sequence-based or graph-based strategies. Sequence-based approaches rely on proximity signals to yield high contiguity, but underutilize assembly graph information, resulting in more structural errors and chromosomal misassignments. Graph-based methods leverage graph topology for higher accuracy but frequently struggle to achieve chromosome-scale contiguity. However, neither strategy alone can overcome its inherent limitations to simultaneously achieve high contiguity and accuracy. To address these challenges, we introduce HapFold, the first hybrid scaffolding framework that synergistically leverages the complementary strengths of both graph-based and sequence-based approaches. By integrating the topological accuracy of assembly graphs with the proximity-guided contiguity of sequence models, HapFold achieves highly accurate, chromosome-scale or near-T2T haplotype reconstructions for diploid genomes. Compared to existing methods, HapFold achieves superior assembly quality while accelerating computation by an order of magnitude. Furthermore, in the haplotype reconstruction of diploid genomes using standard Oxford Nanopore Technologies simplex reads, HapFold enables the reconstruction of a greater number of near-T2T assemblies. Our approach provides a robust and scalable solution for the high-fidelity reconstruction of haplotype-resolved diploid genomes.

bioinformatics↗

bioRxiv2026

Pervasive co-option of prokaryotic adenine methyltransferases by eukaryotic retrotransposons

Cytosine DNA methylation is broadly associated with transposable element silencing across eukaryotes, whereas 6-methyladenine (6mA) in unicellular eukaryotes is linked to actively transcribed chromatin. How transposable elements adapt to these contrasting epigenetic environments remains largely unexplored. Here we identify widely distributed eukaryotic retrotransposons encoding prokaryotic-like DNA adenine methyltransferases (DAMs). Phylogenetic analyses indicate a single ancestral acquisition from prokaryotes followed by recurrent transfers between retrotransposon classes across diverse eukaryotes. DAM-carrying LTR elements are preferentially found in species encoding AMT1, the main eukaryotic 6mA methyltransferase, and show elevated 6mA levels relative to other LTR retrotransposons in multiple lineages, accompanied by increased transcription. We further identify retrotransposons combining adenine and cytosine methyltransferases with chromodomains, indicating the assembly of unexpectedly complex epigenetic toolkits within single retrotransposon units. These findings suggest that retrotransposons have repeatedly co-opted prokaryotic-like methyltransferases to exploit host 6mA-associated chromatin, highlighting adaptation to host epigenetic landscapes as a major driver of transposable element evolution.

genomics↗

bioRxiv2026

Epistasis of two classical color genes, B and L-2, synergistically controls carotenoid accumulation in squash

Carotenoid accumulation underlies fruit color and nutritional quality in squash (Cucurbita pepo). One pair of dominant genes, B and L-2, have been long known to interact epistatically, substantially boosting carotenoid accumulation and producing intensely orange-fleshed fruit. However, their molecular identities and regulatory mechanism are unknown. Here, we show that B encodes a truncated H subunit of magnesium chelatase (CpCHLHB) and L-2 encodes a homolog of Arabidopsis Pseudo-Response Regulator 2 (CpAPRR2-A). Significantly, expression of phytoene synthase (CpPSY-A), which encodes the major rate-limiting enzyme in carotenoid biosynthesis, was dramatically upregulated in fruit of B/B L-2/L-2 plants compared with b/b L-2/L-2 or B/B l-2/l-2, showing that the B and L-2 interaction affects CpPSY-A transcription. A similar upregulation was also observed in Arabidopsis gun5 L-2 transgenic plants, where gun5 is a genetic mimic of the C. pepo B gene. The wild-type CpCHLHb physically interacted with CpAPRR2-A, attenuating the CpAPRR2-A-mediated activation of CpPSY-A. In contrast, the truncated CpCHLHB lost its ability to interact with CpAPRR2-A, enabling CpAPRR2-A to activate CpPSY-A and produce intensely orange fruit. These findings uncover the mechanism underlying the epistatic interaction through which B and L-2 act synergistically to boost carotenoid production, offering novel mechanistic insights and key targets for improving crop quality. One-sentence summarySynergistic epistasis between B and L-2 arises from loss of interaction between their encoded proteins, resulting in dramatically upregulating the key rate-limiting enzyme in carotenoid biosynthesis pathway to produce intensely orange-fleshed fruit in squash.

plant biology↗

bioRxiv2026

Identification of Reductases Catalyzing Benzyl Alcohol Formation during Salicylic Acid Biosynthesis in Plants

Salicylic acid (SA), a central hormone in plant immunity, is biosynthesized via a recently elucidated phenylalanine-derived pathway in most seed plants. This pathway requires benzyl alcohol as a key substrate for the formation of the SA precursor benzyl benzoate. However, how benzyl alcohol is produced in plants was unclear. Here, we identify a two-step conversion of benzoyl-CoA to benzyl alcohol via benzaldehyde in Nicotiana (N.) benthamiana. From a forward genetic screen for SA-deficient mutants, the and {beta} subunits of heterodimeric benzaldehyde synthase (BalS) involved in the conversion of benzoyl-CoA to benzaldehyde were found to be required for SA biosynthesis in N. benthamiana. Further reverse genetic analysis revealed that the NADPH-dependent benzaldehyde reductase (BalR1) acts downstream of BalS to convert benzaldehyde to benzyl alcohol. Interestingly, OsBalR1, but not OsBalS or OsBalS{beta}, is required for maintaining high basal SA levels in rice, suggesting the presence of redundant benzoyl-CoA-reducing activities or alternative biosynthesis routes for benzyl alcohol production. Together, this work defines the missing enzymatic steps in phenylalanine-derived SA pathway and provides insights into the evolutionary diversification of SA production strategies in plants.

plant biology↗

bioRxiv2026

G-SPRI: A Structure-Centric Graph Model for Comprehensive Prediction of Cancer Driver Events from Missense Mutations

In silico approaches for predicting the functional impact of missense mutations are critical for interpreting personal genomes and identifying disease-related biomarkers. Existing methods largely rely on sequence-based information or intuitive structural features, but often overlook the complex biophysical patterns encoded in protein 3D structures. Here, we present G-SPRI, a multilevel framework built on a novel alpha-shape protein graph that accurately captures residue connectivity from atomic-resolution geometry and enables precise message passing around mutation sites. Using this graph representation, G-SPRI integrates wild-type structural properties and mutation-specific perturbation signals derived from the Protein Data Bank (PDB) universe to support graph-based learning for distinguishing pathogenic from benign missense variants. G-SPRI performs strongly across multiple key tasks. On the binary prediction benchmark, G-SPRI delivers improved pathogenicity prediction for individual mutations. By integrating mutation recurrence across the pan-cancer cohort, G-SPRI recovers more known cancer driver genes than state-of-the-art methods from more than 2.3 million mutations. Furthermore, by jointly quantifying site-specific pathogenicity and co-clustering influence within higher-order structural organization units, G-SPRI provides comprehensive evidence for pinpointing likely driver mutations and structurally susceptible regions within disease genes.

bioinformatics↗

bioRxiv2026

Rodent-driven NO3--N enrichment reshapes amoeba--bacteria co-occurrence and bacterial functional potential in burrow soils

Interactions between amoebae and bacteria are increasingly viewed as key drivers of zoonotic pathogen emergence in rodent-dwelling burrows, yet the environmental factors shaping these interactions remain poorly understood. Here, we analyzed soil characteristics and used absolute quantitative high-throughput sequencing to assess microbial communities in active burrow, inactive burrow, and off-burrow soils across four rodent species (marmot, squirrel, gerbil, and vole) in the Hulunbuir grassland of Inner Mongolia, China. This study demonstrates that rodent activity creates chemically distinct soil microhabitats, with nitrate (NO --N) enrichment in active burrow soils consistently observed across rodent species. Elevated soil NO3--N was associated with reduced microbial phylogenetic diversity and reorganization of amoeba-co-occurring bacterial assemblages. Both absolute abundance-based correlations and functional prediction of co-occurring bacteria indicated that amoebae were primarily associated with nitrogen-cycling bacteria in off-burrow soils. In burrow soils, amoebae increasingly interacted with bacterial taxa associated with pathogenicity while retaining ties to nitrogen-cycling taxa. Structural equation modeling and mediation analysis revealed that NO3--N enrichment indirectly linked to increased infectious disease-related functional potential by amoeba-associated bacterial restructuring and coordinated shifts in nitrogen cycling, independent of changes in bacterial abundance. Together, our findings highlight the importance of rodent-driven soil heterogeneity in shaping amoeba-bacteria interactions and suggest that rodent-mediated NO --N enrichment may promote the emergence and persistence of potentially pathogenic bacteria, with broader implications for soil ecosystem functioning and disease-related processes in terrestrial ecosystems.

ecology↗

bioRxiv2026

An expansive animal gut microbiome dataset elucidates major compositional shifts across bilaterian evolution

Animal gut microbiomes provide key physiological functions and are critical for host health. They vary dramatically across the animal kingdom, and are shaped by factors including host diet, evolutionary history and environment. However, analyses of gut microbiomes spanning the entire metazoan clade are lacking, limiting our understanding of the fundamental principles governing gut microbiomes. Here we present the Gut Microbiome Tree of Life (GMToL), a curated 16S amplicon dataset of 17,366 samples from 1,553 host species across 26 host classes from 284 studies, enabling analysis of large-scale evolutionary trends. Using ancestral state reconstruction, we provide a critical baseline calculation of major compositional shifts in gut microbiomes throughout animal evolution. We show that the ancestral animal gut was likely dominated by Pseudomonadota. A major shift to Bacteroidota occurred during the evolution of tetrapods, followed by the emergence of Bacillota-dominated guts in mammals and birds. We identify conserved core gut microbes and demonstrate how GMToL can be leveraged to contextualize the evolutionary history of specific microbial taxa. Ultimately, this framework enables the predictive mapping of microbial symbionts across uncharacterized host lineages, and establishes a quantitative baseline for comparative microbiome research at scale.

microbiology↗

bioRxiv2026

EnzCast: Prediction of Patient-Specific Enzymatic Kinetics through Multi-Modal Deep Learning and Isoform-Resolved Bayesian Inference based on Single-Cell Transcriptomics

Enzyme kinetic parameters underpin mechanistic biology but remain sparse in physiological context. We present EnzCast, a multi-modal framework jointly predicting Km, kcat, kcat/Km, and Ki from protein sequence, 3D structure, substrate chemistry, and experimental conditions, paired with IsoKin, an isoform-resolved Bayesian framework converting EnzCast priors into patient-specific in vivo kinetics. Trained on KinBench, the largest curated kinetics database, task-adaptive EnzCast achieved R2 = 0.413, 0.455, 0.227, and 0.105 for Km, Ki, kcat, and kcat/Km, surpassing all baselines on catalytic tasks. Systematic condition scans recovered compartment-specific pH direction inversion and pathway-level temperature responses. In a 20-patient colorectal cancer single-cell cohort, IsoKin reduced posterior uncertainty by 73.3% and 77.3%, revealing cell-type-specific rewiring. Orthogonal validation--scFEA flux, DepMap essentiality (permutation P = 0.0008) and TCGA survival-- provided mixed but directionally consistent support. Together, EnzCast and IsoKin bridge in vitro prediction, condition-aware biochemical interrogation and patient-resolved in vivo inference.

bioinformatics↗

bioRxiv2026

The structural basis of RanGAP1 regulation and catalysis in nuclear transport

RanGAP1 promotes GTP hydrolysis of nuclear pore complex (NPC) transport complexes at the cytoplasmic face. A disordered linker connects its catalytic GAP domain to the C-terminal sumoylation domain, anchoring into NPCs cytoplasmic filaments. This arrangement raises the question of how these distinct functions are coordinated within a crowded cellular environment. Using atomistic molecular dynamics simulations, we show that RanGAP1 adopts an autoinhibited conformation, where the C-terminal domain masks the catalytic GAP domain. Sumoylation allosterically relieves this autoinhibition, enabling GTP-bound Ran access to the GAP domain. In the cytosol, Ran-GTP/RanBP1 can bind a less populated open conformation of RanGAP1, providing a backup mechanism for GTP hydrolysis in Ran. Importantly, we observe that Arg191 of human RanGAP1 inserts into the GTP-binding pocket of Ran and directly interacts with the {gamma}-phosphate, consistent with a canonical arginine finger. This observation contrasts with earlier models derived from yeast RanGAP and suggests that human RanGAP1 may follow a catalytic mechanism similar to classical small GTPase regulators like NF1. Together, these findings provide a framework of RanGAP1, linking autoinhibition, sumoylation, spatial organization at the NPC, and the catalytic mechanism. They also highlight how conformational regulation and post-translational modification coordinate efficient GTP hydrolysis in Ran during nuclear transport.

biophysics↗

bioRxiv2026

HuR Regulates GATA3-Driven Type 2 Inflammation in CD4⁺ T cells and ILC2 in Airway Inflammation

Type 2-high asthma is driven by coordinated GATA3-dependent programs in CD4 T cells and group 2 innate lymphoid cells (ILC2). Although biologics targeting Th2 cytokines benefit subsets of patients, many remain symptomatic, suggesting upstream regulatory mechanisms may sustain type 2 inflammation. We investigated whether the RNA-binding protein HuR (ELAVL1) functions as a post-transcriptional regulator of GATA3-driven type 2 inflammation in allergic asthma. Using a house dust mite (HDM) model in vivo, HuR inhibition with KH-3 reduced lung inflammation, suppressed Th2 cytokine expression, accelerated Gata3 mRNA decay in lung CD4 T cells, and attenuated airway hyperresponsiveness toward control levels. In ex vivo-activated human lung CD4 T cells, KH-3 accelerated GATA3 mRNA decay with minimal effects on RORC or TBX21 and selectively reduced Th2 cytokine secretion, while IL-10 and IL-2 were unchanged. Similarly, ILC2s isolated from PBMCs of type 2-high asthmatic donors showed reduced GATA3 mRNA stability and diminished Th2 cytokine production following KH-3 treatment. Single-cell transcriptomic analysis of bronchoalveolar lavage fluid after allergen challenge in asthmatic subjects demonstrated co-enrichment of ELAVL1 and GATA3 within Th2 clusters in human airways. Together, these findings identify HuR as a therapeutically targetable upstream regulator of GATA3-driven type 2 inflammation in allergic asthma.

immunology↗

bioRxiv2026

Repetition-controllable gain-managed nonlinear fiber amplifier enables ultrashort, multiphoton imaging with reduced photodamage

1.We report a repetition-controllable gain-managed nonlinear fiber amplifier (GMNA) that delivers near-infrared 50-fs pulses with pulse energies up to 150 nJ and a widely tunable repetition rate from 1-20 MHz, while maintaining stable pulse quality across the full range. Using this source, we demonstrate label-free multiphoton imaging--including metabolic autofluorescence (2PF/3PF), second/third-harmonic generation, and Simultaneous Label-free Autofluorescence Multiharmonic (SLAM) microscopy imaging--across live cells, human lung spheroids, and hard tissues. We further assess the impact of laser repetition rate on photodamage at fixed pulse energy, supported by preliminary measurements indicating lower damage at lower repetition rate. Collectively, the compact architecture and repetition-rate agility of the GMNA enable real-time optimization of imaging speed, depth, and sample safety for advanced biological microscopy.

biophysics↗

bioRxiv2026

PanVariants: Best Practice for Pangenome-based Variant Calling Pipeline and Framework

BackgroundAlthough pangenome references offer richer population diversity compared to linear references, current mainstream pangenome-based variant callers are limited to detecting only known variants stored in the graph. To address this limitation, we developed PanVariants, a novel pipeline designed to improve the detection of both known and novel variants accurately. We systematically evaluated its performance against the traditional linear alignment solution (BWA+GATK/Manta) and the existing pangenome-aware solution (DRAGEN/PanGenie) in three contexts: small variants (SNVs/indels) and structural variants (SVs) accuracy in Genome in a Bottle samples, clinical detection on positive samples, and application in cohort-based joint calling. ResultsBy integrating k-mer-based and mapping-based methods, PanVariants significantly reduced variant errors (FPs + FNs), achieving a 73% reduction compared to BWA+GATK and a 45% reduction compared to DRAGEN for SNVs. Retraining the DeepVariant model with high-quality DNBSEQ data further decreased errors by 15%. For SVs detection, PanVariants attained an F1-score of 89.39%, markedly outperforming DRAGEN (68.18%) and BWA+Manta (58.33%), approaching long-read sequencing performance (95.22%). In validation using clinical positive samples, PanVariants successfully detected all expected pathogenic variants while PanGenie failed. In the cohort joint-calling analysis, PanVariants detected more variants, made fewer Mendelian inheritance errors, and gave better per-sample accuracy than GATK. ConclusionsPanVariants establishes a robust framework and best-practice pipeline for pangenome-based variant detection, achieving both sensitive novel variant discovery and high accuracy for SNVs, indels and SVs. Our systematic evaluation of optional processing steps and input variables offers practical guidance for users. Validated across diagnostic and population-based applications, our findings strongly support the transition from linear to pangenome references in future genomics.

bioinformatics↗